Semiparametric distributed lag quantile regression for modeling time-dependent exposure mixtures

Studying time-dependent exposure mixtures has gained increasing attentions in environmental health research. When a scalar outcome is of interest, distributed lag (DL) models have been employed to characterize the exposures effects distributed over time on the mean of final outcome. However, there is a methodological gap on investigating time-dependent exposure mixtures with different quantiles of outcome. In this paper, we introduce semiparametric partial-linear single-index (PLSI) DL quantile regression, which can describe the DL effects of time-dependent exposure mixtures on different quantiles of outcome and identify susceptible periods of exposures. We consider two time-dependent exposure settings: discrete and functional, when exposures are measured in a small number of time points and at dense time grids, respectively. Spline techniques are used to approximate the nonparametric DL function and single-index link function, and a profile estimation algorithm is proposed. Through extensive simulations, we demonstrate the performance and value of our proposed models and inference procedures. We further apply the proposed methods to study the effects of maternal exposures to ambient air pollutants of fine particulate and nitrogen dioxide on birth weight in New York University Children's Health and Environment Study (NYU CHES).     

Contribution of the residue at position 4 within classical nuclear localization signals to modulating interaction with importins and nuclear targeting

Nuclear import involves the recognition by importin (IMP) superfamily members of nuclear localization signals (NLSs) within protein cargoes destined for the nucleus, the best understood being recognition of classical NLSs (cNLSs) by the IMPα/β1 heterodimer. Although the cNLS consensus [K-(K/R)-X-(K/R) for positions P2–P5] is generally accepted, recent studies indicated that the contribution made by different residues at the P4 position can vary. Here, we apply a combination of microscopy, molecular dynamics, crystallography, in vitro binding, and bioinformatics approaches to show that the nature of residues at P4 indeed modulates cNLS function in the context of a prototypical Simian Virus 40 large tumor antigen-derived cNLS (KKRK, P2–5). Indeed, all hydrophobic substitutions in place of R impaired binding to IMPα and nuclear targeting, with the largest effect exerted by a G residue at P4. Substitution of R with neutral hydrophobic residues caused the loss of electrostatic and van der Waals interactions between the P4 residue side chains and IMPα. Detailed bioinformatics analysis confirmed the importance of the P4 residue for cNLS function across the human proteome, with specific residues such as G being associated with low activity. Furthermore, we validate our findings for two additional cNLSs from human cytomegalovirus (HCMV) DNA polymerase catalytic subunit UL54 and processivity factor UL44, where a G residue at P4 results in a 2–3-fold decrease in NLS activity. Our results thus showed that the P4 residue makes a hitherto poorly appreciated contribution to nuclear import efficiency, which is essential to determining the precise nuclear levels of cargoes.